Author

Jia-Chuan Wang

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Preprint Sep 2026

Learning Multimodal Embeddings with Evidence-Aligned Readout

Multimodal large language models can expose task-relevant evidence through generation, but producing useful evidence does not by itself determine how it enters a retrieval embedding. We study whether the semantic organization of that evidence can also specify where representations are read. To address this question, we...

Zi-Rong Chen, Fu-Da Ye, En-Jun Du et al. · 1 citation

#artificial intelligence Preprint Sep 2026

TEAR: Table Extraction with Attribute Recommendation from Texts via Large Language Models

TEAR is the first framework that supports automated text-driven attribute recommendation, enabling exploratory schema design for table extraction and attribute recommendation on naturally occurring texts and achieves state-of-the-art performance on both tasks.

Tong Li, Shu-Ye Ding, Jia-Chuan Wang et al. · 0 citations